GEO (generative engine optimization) is gonna shake up the SEO...

GEO (generative engine optimization) is gonna shake up the SEO industry...

i just done a deep dive on...
- the difference between SEO & GEO
- why SEO still matters, but it's not the whole equation
- the GEO process from prompt -> subqueries -> citing
- how to increase the likelihood of LLM's citing your content
- the most important thing you can do for your content/brand to be cited by LLM's

& i'm sharing all my findings with you...

THE DIFFERENCE BETWEEN SEO & GEO:

traditional SEO = optimize for ranking in search results
GEO = optimizing for inclusion in LLM answers - your content being cited by AI

the world is shifting from traditional search engines -> LLM’s for their questions

it's rare that any moderately tech-savvy person will go to google to figure out how to solve a problem nowadays

this also means that the queries being searched are now longer, sessions are more context-rich, & results are more personalized and conversational

WHY SEO STILL MATTERS A LOT…

generative systems use retrieval-augmented generation (RAG) to scrape content

that means when you ask a question:
- the LLM searches (its own training data, or when it needs to scrape the web it's usually bing)
- it retrieves top-ranking, high-quality pages
- it summarizes or quotes from those pages

that means that if your page doesn’t rank well, or isn’t retrievable, it won’t even get considered as a source - so ranking in search results is still a gateway to being in the AI’s retrieval set...

the difference now though is that AI retrieval and generation systems don't always just pull the #1 result, instead they:
- pull multiple top results (e.g. top 5, 10, or 20)
- prefer pages with clear, extractable answers
- weigh semantic relevance over exact match rankings

for example: a page ranked #5 but with a crystal-clear, well-structured answer might get quoted over #1 if #1 is vague & not too relevant to the original query

THE GEO PROCESS:

- user asks the LLM a query (prompt)
- LLM decides keywords to search up by breaking up longer query into subqueries
- if the subquery doesn’t need to be searched, it’ll just pull info from its training data
- if the LLM decides that it does need to be searched it uses RAG to retrieve relevant info from the index (ChatGPT uses bing to search)
- the content that is most well-structured, relevant & optimized for AI readability gets injected into the context window
- the LLM will cite different parts from multiple sources

HOW TO INCREASE YOUR CHANCES OF RANKING:

make sure your site is properly crawlable

your website must be indexed and rank well in Bing

ensure clear site structure - AI will favor well-organized & direct content, use headings, bullet points & FAQs

use specific data and statistics (ChatGPT loves citing these)

use firsthand experience (case studies, personal reviews)

cite authoritative sources makes your content more "attractive" for inclusion

AI prefers original, specific, and quotable content

make sure the content is very clear, clarity wins as it needs to be AI-friendly

optimize your content for question-based queries (e.g. “How to rank my YouTube video” rather than “YouTube ranking tutorial”)

LLM’s prefer sources from high-authority sources - so include credentials & citations in your content

summaries & bullet pointed content get favored by LLM crawlers

your brand/business being mentioned on high authority sites like reddit & quora will increase likelihood of being cited in outputs

THE IMPORTANCE OF YOUR BRAND BEING "FINDABLE":

LLM's are trained on a massive slice of the Internet...

the more your brand is mentioned across many sites, the more it learns about you...

this helps in real-time searches (background web searches) & static responses from its training data (when it doesn’t search live)

ensure that your brand gets coverage on mainstream media, niche publications, blogs, forums, etc.